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The model produced an accuracy of 53% with 70.8% specificity and 27.6% sensitivity.
Results showed that the model produced an excellent fit to the relative wind speed (i.e. normalized by ambient wind speed) with root-mean-square error of 4% ± 0.5%.
When applied to a database of 24 tests, the model produced an average shear strength experimental-to-predicted ratio of 1.12 with a coefficient of variation of 8.4%.
Finally, a linear biphasic model produced an aggregate modulus of 2.58±0.87 kPa, a permeability of 2.57×10−12±3.09 m4/N-s, and a Poisson's ratio of 0.069±0.021.
The former model produced an average shear strength experimental-to-predicted ratio Vexp/Vpred of 1.00 with a coefficient of variation (COV) of 19.8%, while the latter resulted in an average of 1.08 with a COV of 15.4%.
The model produced an accuracy of 86%.
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This model produced a big success in Miami.
Findings confirmed that the SCCT model produced a good fit to the data across gender.
The inverted model produced a high resolution depiction of the hydraulic conductivity and porosity fields.
The logistic regression model produced a nagelkerke R2 of 16.6%.
This modular industrial model produced a redefinition of design methods.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com